The angular mean of voter scoring vectors satisfies long-run individual proportionality for sequential linear ranking decisions.
High-dimensional statistics: A non-asymptotic viewpoint
2 Pith papers cite this work. Polarity classification is still indexing.
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ACTS improves Thompson sampling in high-dimensional Bayesian optimization by adaptively reducing the search space using gradients from surrogate samples to produce better maximizer samples.
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The End Justifies the Mean: A Linear Ranking Rule for Proportional Sequential Decisions
The angular mean of voter scoring vectors satisfies long-run individual proportionality for sequential linear ranking decisions.
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Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization
ACTS improves Thompson sampling in high-dimensional Bayesian optimization by adaptively reducing the search space using gradients from surrogate samples to produce better maximizer samples.